Pistoia Alliance October Virtual Conference: Leveraging Latent Knowledge to Investigate a Pandemic
This is part of the Pistoia Alliance Collaborate to Innovate Virtual Conference Week, October 19-23, 2020. For more information about related events, please visit our online calendar.
Unsupervised embedding techniques have been shown to capture complex concepts from unstructured data such as published texts and electronic health records. Applying these machine learning methods to structured, expert-curated content from the scientific literature can be even more powerful.
Building on the QIAGEN Knowledge Base, we use this approach to infer new disease-gene associations and build disease models that can be applied to drug repurposing. The presentation will focus on a case study in which new SARS-CoV-2 research was combined with a knowledge graph and machine learning models to create the Coronavirus Network Explorer, a free collection of interactive networks depicting how viral proteins interact with host proteins to impact a variety of host cell functions.
At the conclusion of this session, participants should be able to:
Senior Vice President, QIAGEN Digital Insights Business Area